Use case · AI email agents

Watch your email agent work before real people see it

Give your agent a mailbox and a world of people who answer in character. Then read what happened: every email, every reply, and why each person did what they did.

simmail · your agent's mailbox
The Mail view: an agent's mailbox with replies from simulated homeowners
Every decision, with its reason

Read the run like a log, in plain words

Activity records everything that happened and why: mail delivered and scored for spam, a person who looked up the sender's domain and found no website, a reply planned for working hours, spam that arrived from the World.

Follow it live, read it from the API, or have it posted to your webhook. Insights sums it up per campaign.

Events and stream · Insights

simmail · activity
The Activity timeline: deliveries, spam scores, a sender look-up and a planned reply
Marcus looked up harborpine.example, found no website, and planned his reply for Monday morning.
A known truth

Check what the agent said against what people remember

Each person keeps their own record of the conversation. Dana remembers the $186,000 offer, and that her requests for paperwork went unanswered. Push a case with the facts, and everyone on it stays consistent with one story your evaluation can read from the API.

Cases · Memory

simmail · Dana Reyes
What Dana Reyes remembers about her conversation with the sender
What Dana remembers, with the time of each line.
Hard cases

The situations agents get wrong

Choose the people and the mail your agent meets, and put the awkward ones in on purpose.

People who push back

Skeptical people question the premise and want proof. Difficult ones negotiate hard and escalate. Ghosts rarely answer at all.

Promises to track

People promise things and sometimes slip. When the agent promises something and misses it, they chase it.

Mail it should not act on

World streams can send spam and phishing into the agent's inbox alongside real leads and support requests.

Silence

A person may decide not to reply. The agent has to handle it like a real silence.

Its own deliverability

Every email the agent writes gets a spam score. Mail over a person's filter lands in Junk and is never answered.

Days, not seconds

Skip the clock ahead to see what the agent does when replies and nudges arrive over a week.

Connect

Connect the agent over MCP, with its own key

Connect the agent over MCP to send, wait for replies, read mailboxes, add people, push cases, check email health and move the clock. Or let it use SMTP, IMAP and the HTTP API like any app. Revoke its key when the experiment ends.

</> For developers: the agent setup
// .mcp.json at your project root (Claude Code)
{
  "mcpServers": {
    "simmail": {
      "type": "http",
      "url": "https://c1.simmail.dev/mcp",
      "headers": { "Authorization": "Bearer ${SIMMAIL_API_KEY}" }
    }
  }
}

Read the docs →

Questions

Are the people’s replies the same on every run?

No. People write with AI, so their wording changes between runs, as real people’s would. What you control is the setup: the people, their temperaments and reply rates, the case facts and the clock. Use a fresh universe per run so memories and relationships start clean.

Can the agent send real mail if it goes wrong?

No. simmail has no relay and no outbound SMTP client. Mail to any address stays inside simmail. Links in the agent’s emails are opened with real web requests, so avoid links that change something when visited.

How do I tell what the agent should have known?

Push a case. simmail writes its story once; the people on it stay consistent with it, and the story never appears in any email. GET /api/cases/{id} reads it, so your evaluation can compare the agent’s conclusions with the truth.

Does my agent have to use MCP?

No. MCP is one way in. The same universe speaks SMTP, IMAP and an HTTP API, so an agent that already sends over SMTP or reads over IMAP works as it is.

What does a run cost?

Each reply a person writes, each person the AI invents, each case story and each inbound World email is one AI action from your plan. When they run out, people answer from templates until the month resets. See Plans and limits.

Put real behaviour between your app and its inbox

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